Generating a High-Precision True Digital Orthophoto Map Based on UAV Images

被引:56
作者
Liu, Yu [1 ]
Zheng, Xinqi [1 ]
Ai, Gang [1 ]
Zhang, Yi [1 ]
Zuo, Yuqiang [2 ]
机构
[1] China Univ Geosci Beijing, Sch Informat Engn, Beijing 100083, Peoples R China
[2] China Land Surveying & Planning Inst, Beijing 100035, Peoples R China
关键词
unmanned aerial vehicle; structure from motion; multi view stereo; digital surface model; true digital orthophoto map; STRUCTURE-FROM-MOTION; UNMANNED AERIAL VEHICLE; PHOTOGRAMMETRY; TOPOGRAPHY; PLATFORMS; SENSORS; TOOL;
D O I
10.3390/ijgi7090333
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Unmanned aerial vehicle (UAV) low-altitude remote sensing technology has recently been adopted in China. However, mapping accuracy and production processes of true digital orthophoto maps (TDOMs) generated by UAV images require further improvement. In this study, ground control points were distributed and images were collected using a multi-rotor UAV and professional camera, at a flight height of 160 m above the ground and a designed ground sample distance (GSD) of 0.016 m. A structure from motion (SfM), revised digital surface model (DSM) and multi-view image texture compensation workflow were outlined to generate a high-precision TDOM. We then used randomly distributed checkpoints on the TDOM to verify its precision. The horizontal accuracy of the generated TDOM was 0.0365 m, the vertical accuracy was 0.0323 m, and the GSD was 0.0166 m. Tilt and shadowed areas of the TDOM were eliminated so that buildings maintained vertical viewing angles. This workflow produced a TDOM accuracy within 0.05 m, and provided an effective method for identifying rural homesteads, as well as land planning and design.
引用
收藏
页数:15
相关论文
共 40 条
  • [1] Assessment of photogrammetric mapping accuracy based on variation ground control points number using unmanned aerial vehicle
    Aguera-Vega, Francisco
    Carvajal-Ramírez, Fernando
    Martinez-Carricondo, Patricio
    [J]. MEASUREMENT, 2017, 98 : 221 - 227
  • [2] A Robust Photogrammetric Processing Method of Low-Altitude UAV Images
    Ai, Mingyao
    Hu, Qingwu
    Li, Jiayuan
    Wang, Ming
    Yuan, Hui
    Wang, Shaohua
    [J]. REMOTE SENSING, 2015, 7 (03) : 2302 - 2333
  • [3] Cao M., 2016, B SURV MAPP, V8, P35
  • [4] Chang B., 1983, J SURV MAPP, V3, P31
  • [5] [陈良浩 Chen Lianghao], 2016, [测绘科学, Science of Surveying and Mapping], V41, P205
  • [6] Unmanned aerial systems for photogrammetry and remote sensing: A review
    Colomina, I.
    Molina, P.
    [J]. ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING, 2014, 92 : 79 - 97
  • [7] Cui Y., 2014, P 7 NAT C CHIN NAT R
  • [8] UAV-based detection and spatial analyses of periglacial landforms on Demay Point (King George Island, South Shetland Islands, Antarctica)
    Dabski, Maciej a
    Zmarz, Anna
    Pabjanek, Piotr
    Korczak-Abshire, Malgorzata
    Karsznia, Izabela
    Chwedorzewska, Katarzyna J.
    [J]. GEOMORPHOLOGY, 2017, 290 : 29 - 38
  • [9] Surface Gradient Approach for Occlusion Detection Based on Triangulated Irregular Network for True Orthophoto Generation
    de Oliveira, Henrique Candido
    Dal Poz, Aluir Porfirio
    Galo, Mauricio
    Habib, Ayman Fawzy
    [J]. IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING, 2018, 11 (02) : 443 - 457
  • [10] Ely J., 2016, EARTH SURF PROCESS L, V42, P877, DOI DOI 10.1002/ESP.4044